Why is data quality so important in CRM?
Does your CRM application contain incomplete, outdated, or duplicate customer data? Undoubtedly, because data quality deteriorates quickly. People change jobs, individuals and businesses relocate, streets are sometimes renamed or renumbered, companies merge or go out of business, organizations change their trade names, and so on.
Without a systematic approach, data quality in your CRM system can go terribly wrong. And poor data quality is detrimental to your marketing, sales, and customer service.
When data quality in CRM is poor:
- In the worst-case scenario, your data will be considered unreliable and therefore simply unusable.
- Your employees will ignore the CRM tool and go back to managing their own lists on their own.
For example, the account manager manages his list of clients and their respective contacts in his own Excel file.
For example, the marketing specialist wants to avoid errors in email campaigns and creates their own lists of email addresses in a separate digital marketing tool that isn't linked to your CRM application.
Consequence: You lose your 360° view of the customer, and your CRM strategy suffers as a result.
Data Quality in Your CRM Application: A Shared Responsibility?
We can say that data quality is everyone’s responsibility. It is certainly true that every employee must do their part to ensure that the data in the CRM is accurate. Nevertheless, we recommend assigning the role of “data manager” to specific employees in your organization. You then give those employees access to the necessary technical tools to work on data quality.
In addition to the technical tools, there is also an action plan is necessary. Please note that there is no “one-size-fits-all” approach to this action plan, as the right action plan varies from organization to organization.
Below is an overview of measures that can be part of an effective action plan to combat poor data quality.
Start at the source: quality for data entry
When entering data, you can automatically assist employees by:
- automatically validate entered data using a consistent format specific data; such as business ID numbers, phone numbers, email addresses, etc. You typically use regular expressions for this.
- where possible, to automatically fill in data as much as possible; such as automatically filling in the municipality and province once the ZIP code is entered.
- to build in consistency rules to prevent invalid data combinations; for example, if the value X is entered in one specific field, then the value Y must be entered in the other field.
- Where possible, use drop-down lists or add auto-suggestions to free-text fields; such as when selecting a country.
- Make the required information mandatory to avoid incomplete input.
An extra tip for required fields: it’s important to strike the right balance so your employees aren’t hindered from creating accounts or contacts in the CRM. For example, you can automatically adjust required fields based on the user profile and the step in the business process. For example, when creating a “sales prospect” in B2B, limit the required fields to first name, last name, email address, job title, and company name. Once this prospect becomes a customer, you can automatically make the billing address and business ID required as well.
End-User Training
Make your end users aware of the importance of data quality (if this is not already the case).
- Explain who in the organization uses the data, for what purposes, and what problems can arise from poor data quality. Set clear expectations regarding the management of contacts so that everyone takes their responsibilities seriously.
- Delegate responsibility whenever possible. It goes without saying that an account manager is responsible for the data quality of their own clients' contacts.
- Set clear rules. What constitutes poor or good data quality? How do you handle abbreviations? For example, “Pvd Wouwerstr.” or “Pastoor Van De Wouwerstraat.” It’s normal for these guidelines to evolve, so be sure to update them as new issues arise.
Reevaluate who is and isn't authorized to manage your contact database
If an end user does not always comply with the terms and conditions, then it is advisable to to adjust the security permissions for that specific user.
Always consider whom you want to grant the rights to:
- Create or edit contacts, accounts, and leads.
- Perform bulk edits, exports for reimport, and imports. There is always a risk that contacts will end up in your CRM application with incorrect data. In any case, these import permissions are not available to every user.
Also, always exercise caution when granting permissions to delete data. It is absolutely essential to ensure that data quality management does not result in data loss. For this reason, we recommend using delete permissions with extreme caution.
Duplicate customer records
Duplicate data causes confusion and results in an incomplete view of the customer if the related data is scattered across two or more customer records. The battle against duplicates is fought on two fronts: prevention and remediation.
Preventive measures:
- When creating or updating a customer record: send an automatic notification to the user that the CRM system has detected a duplicate.
- When contact information is imported automatically (e.g., via an online form), ensure that the system automatically searches for potential matches (using either an exact or fuzzy search). This allows the system to link the existing contact instead of creating a new duplicate contact.
Even if everyone does their best… “duplicates happen” ;-). And then there’s no choice but to resolve the duplicates. How do you do that? By regularly running duplicate detection in your CRM application. Review the duplicates found and merge them (i.e.,. merge duplicates). When merging duplicate records, select the primary record to which all related data should be re-linked. At the record level, you can even specify, on a field-by-field basis, which information you want to include in the merged record.
Integration with third-party data sources
A powerful way to ensure the accuracy of customer data is to integrate your CRM application with other reliable data sources. This allows you to automatically enrich, correct, and keep customer data up to date.
Here are a few examples of reliable data sources that you might want to integrate (depending on your specific business objectives):
• Top Trends
• Enhanced Cross-Reference Database of Businesses
• Graydon
• LinkedIn Sales Navigator. For example, there is a standard integration option between Dynamics 365 and LinkedIn Sales Navigator More info
• …
Create a Sustainable Action Plan
Data quality is not a one-time project, but an ongoing responsibility for a data manager and every employee with the necessary permissions to manage data.
Tasks that the data manager must perform on a regular basis:
- Run Advanced Find queries on Contacts, Leads, and Accounts with missing or incorrect data to identify records with poor data quality.
- Perform duplicate detection.
What if an employee discovers a data quality issue but doesn’t have the necessary permissions to resolve it? You could give regular users the ability to flag records in your CRM application so the data manager can review them. Of course, the lists of flagged records must also be monitored regularly.
Conclusion
The data quality in your CRM application is invaluable! So get started right away with the tips in this blog post to keep your CRM data reliable and usable.
